Method and apparatus for generating and using enhanced tree bitmap data structures in determining a longest prefix match

ABSTRACT

Methods and apparatus are disclosed for generating and using an enhanced tree bitmap data structure in determining a longest prefix match, such as in a router, packet switching system. One implementation organizes the tree bitmap to minimize the number of internal nodes that must be accessed during a lookup operation. A pointer is included in each of the trie or search nodes to the best match so far entry in the leaf or results array which allows direct access to this result without having to parse a corresponding internal node. Moreover, one implementation stores the internal node for a particular level as a first element in its child array. Additionally, one implementation uses a general purpose lookup engine that can traverse multiple tree bitmaps or other data structures simultaneously, and perform complete searches, partial searches, and resume partial searches such as after receiving additional data on which to search.

CROSS-REFERENCE TO RELATED APPLICATIONS

This is a divisional of application Ser. No. 10/161,504, filed May 31,2002, and hereby incorporated by reference.

FIELD OF THE INVENTION

This invention especially relates to communications and computersystems; and more particularly, the invention relates, but is notlimited to generating and using enhanced tree bitmap data structures indetermining a longest prefix match, such as in a router, packetswitching system, or other communications or computer system.

BACKGROUND OF THE INVENTION

The communications industry is rapidly changing to adjust to emergingtechnologies and ever increasing customer demand. This customer demandfor new applications and increased performance of existing applicationsis driving communications network and system providers to employnetworks and systems having greater speed and capacity (e.g., greaterbandwidth). In trying to achieve these goals, a common approach taken bymany communications providers is to use packet switching technology.Increasingly, public and private communications networks are being builtand expanded using various packet technologies, such as InternetProtocol (IP).

A network device, such as a switch or router, typically receives,processes, and forwards or discards a packet based on one or morecriteria, including the type of protocol used by the packet, addressesof the packet (e.g., source, destination, group), and type or quality ofservice requested. Additionally, one or more security operations aretypically performed on each packet. But before these operations can beperformed, a packet classification operation must typically be performedon the packet.

IP forwarding requires a longest matching prefix computation at wirespeeds. The current IP version, IfPv4, uses 32 bit destination addressesand a core Internet router can have over 200,000 prefixes. A prefix istypically denoted by a bit string (e.g., 01*) followed by a ‘*’ toindicate the value of these trailing bits does not matter. Fordestination routing, each prefix entry in a routing table typicallyconsists of a prefix and a next hop value. For example, suppose thedatabase consists of only two prefix entries (01*→L1;0100*→L2). If therouter receives a packet with destination address that starts with01000, the address matches both the first prefix (01*) and the secondprefix (0100*). Because the second prefix is the longest match, thepacket should be sent to next hop L2. On the other hand, a packet withdestination address that starts with 01010 should be sent to next hopL1. The next hop information will typically specify an output port onthe router and possibly a data link address.

FIG. 1A illustrates an example of a set of prefixes P1-9 shown as nodes1A-9A in table 10A and as nodes 1B-9B in unibit trie 10B. Also shown inunibit trie 10B are placeholder/vacant nodes 11B-18B, which representnon-matching nodes (i.e., nodes that are not possible results as alongest matching prefix.) For example, a string of 1110000 matchesprefixes P1 (1B), P2 (2B) and P5 (5B), with the longest matching prefixbeing P5 (B5).

One known approach is typically referred to as “tree bitmap”, describedin Eatherton et al., “Data Structure Using a Tree Bitmap and Method forRapid Classification of Data in a Database,” U.S. patent applicationSer. No. 09/371,907, filed Aug. 10, 1999, currently pending, which ishereby incorporated by reference. Tree bitmap is a multibit triealgorithm that implements a representation of the trie by grouping nodesinto sets of strides. A stride is typically defined as the number oftree levels of the binary trie that are grouped together or as thenumber of levels in a tree accessed in a single read operationrepresenting multiple levels in a tree or trie. FIG. 1B illustrates onesuch partitioning of nodes P1-P9 (1B-9B) and vacant nodes 11B-18B (FIG.1A) into strides 20-25. In this example, the stride is of size three.

In a known implementation of the tree bitmap algorithm, all child nodesof a given trie node are stored contiguously, which allows the use ofjust one pointer for all children (the pointer points to the start ofthe child node block), as each child node can be calculated as an offsetfrom the single pointer. This can reduce the number of required pointersand cuts down the size of trie nodes.

In addition, there are two bit maps per trie node, one for all theinternally stored prefixes and one for the external pointers. Theinternal bit map has a 1 bit set for every prefixes stored within thisnode. Thus, for an r-bit trie node, there are (2 ^(r))-1 possibleprefixes of lengths less than r, and hence, a (2 ^(r))-1 bit map isused. The external bit map contains a bit for all possible 2 ^(r) childpointers. A trie node is of fixed size and only contains an externalpointer bit map, an internal next hop information bit map, and a singlepointer to the block of child nodes. The next hops associated with theinternal prefixes are stored within each trie node in a separate arrayassociated with this trie node. For memory allocation purposes, resultarrays are normally an even multiple of the common node size (e.g. with16-bit next hop pointers, and 8-byte nodes, one result node is neededfor up to four next hop pointers, two result nodes are needed for up to8, etc.) Putting next hop pointers in a separate result arraypotentially requires two memory accesses per trie node (one for the trienode and one to fetch the result node for stored prefixes). A simplelazy strategy to not access the result nodes till the search terminatesis typically used. The result node corresponding to the last trie nodeencountered in the path that contained a valid prefix is then accessed.This adds only a single memory reference at the end besides the onememory reference required per trie node.

FIG. 1C illustrates one representation of a tree bitmap implementationof the prefix example shown in FIGS. 1A-B. As shown, root node 30represents the first level trie. Child pointer 31 connects root node 30to child array 40 containing the second level strides. In level 3, thereare two child arrays 50 and 60, which are connected from child array 40respectively by child pointers 41 and 42.

A longest prefix match is found by starting with the root node. Thefirst bits of the destination address (corresponding to the stride ofthe root node, three in this example) are used to index into theexternal bit map at the root node at say position P. If a 1 is locatedin this position, then there is a valid child pointer. The number of 1'snot including and to the left of this 1(say I) is determined. Becausethe pointer to the start position of the child block (say C) is knownand the size of each trie node (say S), the pointer to the child nodecan be computed as C+(I * S).

Before moving on to the child, the internal bit map is checked to see ifthere is a stored prefix corresponding to position P. To do so, imaginesuccessively remove bits of P starting from the right and index into thecorresponding position of the internal bit map looking for the first 1encountered. For example, suppose P is 101 and a three bit stride isused at the root node bit map. The right most bit is first removed whichresults in the prefix 10*. Because 10* corresponds to the sixth bitposition in the internal bit map, a check is made to determine if thereis a 1 in that position. If not, the right most two bits (resulting inthe prefix 1*) are removed. Because 1* corresponds to the third positionin the internal bit map, a check is made to determine if a 1 is there.If a 1 is found there, then the search ends. If a 1 is not found there,then the first three bits are removed and a search is performed for theentry corresponding to * in the first entry of the internal bit map.

Once it has been determined that a matching stored prefix exists withina trie node, the information corresponding to the next hop from theresult node associated with the trie node is not immediately retrieved.Rather, the number of bits before the prefix position is counted toindicate its position in the result array. Accessing the result arraywould take an extra memory reference per trie node. Instead, the childnode is examined while remembering the stored prefix position and thecorresponding parent trie node. The intent is to remember the last trienode T in the search path that contained a stored prefix, and thecorresponding prefix position. When the search terminates (i.e., a trienode with a 0 set in the corresponding position of the external bit mapis encountered), the result array corresponding to T at the positionalready computed is accessed to read off the next hop information.

FIG. 1D illustrates pseudocode of one implementation of the full treebitmap search. It assumes a function treeFunction that can find theposition of the longest matching prefix, if any, within a given node byconsulting the internal bitmap. “LongestMatch” keeps track of a pointerto the longest match seen so far. The loop terminates when there is nochild pointer (i.e., no bit set in external bit map of a node) uponwhich the lazy access of the result node pointed to by LongestMatch isperformed to get the final next hop. The pseudocode assumes that theaddress being searched is already broken into strides and stride[i]contains the bits corresponding to the i^(th) stride.

Keeping the stride constant, one method of reducing the size of eachrandom access is to split the internal and external bitmaps, which issometimes referred to as split tree bitmaps. This is done by placingonly the external bitmap in each trie node. If there is no memorysegmentation, the children trie nodes and the internal nodes from thesame parent can be placed contiguously in memory. If memory segmentationexists, it is a bad design to have the internal nodes scattered acrossmultiple memory banks. In the case of segmented memory, one option isfor a trie node to have pointers to the child array, the internal node,and to the results array.

An alternative, as illustrated in FIG. 1E, has the trie node point atthe internal node, and the internal node point at the results array. Tomake this optimization work, each child must have a bit indicating ifthe parent node contains a prefix that is a longest match so far. Ifthere was a prefix in the path, the lookup engine records the locationof the internal node (calculated from the data structure of the lastnode) as containing the longest matching prefix thus far. Then, when thesearch terminates, the corresponding internal node is accessed and thenthe results node corresponding to the internal node is accessed. Noticethat the core algorithm accesses the next hop information lazily; thesplit tree algorithm accesses even the internal bit map lazily. Whatmakes this work is that any time a prefix P is stored in a node X, allchildren of X that match P can store a bit saying that the parent has astored prefix. The software reference implementation uses thisoptimization to save internal bit map processing; the hardwareimplementations use it only to reduce the access width size (because bitmap processing is not an issue in hardware). A nice benefit of splittree bitmaps is that if a node contained only paths and no internalprefixes, a null internal node pointer can be used and no space will bewasted on the internal bitmap.

With this optimization, the external and internal bitmaps are splitbetween the search node and the internal node respectively. Splittingthe bitmaps in this way results in reduced node size which benefitshardware implantations. Each Search node Sj has two pointers—onepointing to the children and the other to the internal node, Ij. Theinternal node Ij maintains a pointer to the leaf array LAj of leavescorresponding to prefixes that belong to this node. For example, FIG. 1Eillustrates search nodes SI (111), S2 (112) and S3 (113), internal nodesI1 (121), 12 (115) and 13 (114), and leaf arrays LA1 (122), LA2 (116)and LA3 (123), and their interconnection by pointers. Additionally, leafarrays LA1 (122), LA2 (116) and LA3 (123) respectively include leafnodes L1 (122A), L2 (116A), and L3 (123A). Note, nodes illustrated insolid lines are the nodes accessed during a tree bitmap lookup exampledescribed hereinafter.

Now, consider the case where a lookup proceeds accessing search nodes S1(111), S2 (112) and S3 (113). If the parent_has_match flag is set in S3(113), this implies there is some prefix in one of the leaf nodes L2(116A) in the leaf array LA2 (116) which is the current longest match.In this case, the address of internal node 12 (115) is saved in thelookup context. Now suppose that S3 (113) is not extending paths forthis lookup. There could be some prefix in leaf array LA3 (123) which isthe longest matching prefix. Hence, 13 (114) is first accessed and itsinternal bitmap checked for a longest matching prefix. If no longestmatching prefix is found, internal node I2 (115), whose address has beensaved, is retrieved, its bitmap parsed, and leaf node L2 (116A)corresponding to the longest match is returned. The above accesssequence is S1 (111), S2 (112), S3 (113), 13 (114), I2 (115), L2 (116A).This example shows that there are cases where two internal nodes need tobe accessed and two internal bitmaps parsed before the longest match canbe determined.

In hardware implementations, the memory access speeds are generally thebottleneck as opposed to node processing time. A typical implementationof a hardware based tree bitmap lookup engine uses multiple memorychannels to store the tree bitmap data structure. In this case the treebitmap nodes are spread out across the memory channels in such a waythat per lookup, successive nodes accessed fall in different memorychannels. If a single memory channel can sustain ‘x’ accesses persecond, then with multiple lookups in progress simultaneously, ‘x’lookups per second on average can be achieved provided each memorychannel is accessed at most once per lookup. If any of the channels isaccessed twice per lookup, then the packet forwarding rate drops by halfbecause that particular channel becomes the bottleneck.

Therefore, all the Internal nodes along any path from root to bottom ofthe tree need to be stored in different memory channels. Accessing twointernal nodes presents a problem when there are a limited number ofmemory channels as both internal nodes need to be placed in differentmemory channels, and which two internal nodes are going to be accesseddepends on the particular tree bitmap and the particular lookup value.Referring to FIG. 1E, for example, the internal nodes accessed could beI3 (114) and I2 (115), or I3 (114) and I1 (121), or I2 (115) and I1(121). Therefore, in this example, all seven nodes S1 (111), S2 (112),S3 (113), I1 (121), I2 (115), I3 (114), and L2 (116) need to be inseparate memory modules. This is problematic when there are less thanseven memory modules.

New methods and apparatus are needed for generating and using enhancedtree bitmap data structures in determining a longest prefix match,especially, but not limited to those methods and apparatus which reducethe number of memory accesses and/or provide an advantage over previoustree bitmap implementations.

SUMMARY OF THE INVENTION

Methods and apparatus are disclosed for generating and using enhancedtree bitmap data structures in determining a longest prefix match, suchas in a router, packet switching system, or other communications orcomputer component, device, or system.

One embodiment traverses a tree data structure stored in one or morecomputer readable mediums based on an input search data string. Oneembodiment performs for each of multiple portions of the input searchdata string a set of steps including: (a) receiving a search progressioncontext of a partially completed tree traversal, the search progressioncontext including a next node address; (b) resuming the traversal of thetree data structure including repeatedly performing steps (i)-(iv) fortraversing the tree data structure corresponding to a next portion ofthe input string: (i) distributing a lookup request including the nextnode address to one of multiple memory devices; (ii) receiving a lookupresult from the one of the multiple memory devices, the lookup resultincluding a search node; (iii) updating a current best match identifierin response to determining if a new best match exists; (iv) indexinginto a current level extending bitmap of the search node to determinewhether or not a matching next level node exists; (v) generating a newvalue of the next node address; and (c) generating a new value for thesearch progression context.

One embodiment traverses a tree data structure stored in one or morecomputer readable mediums based on an input search data string. Oneembodiment includes a tree bitmap next address mechanism for determininga memory address of a next node of a particular tree data structure ofthe tree data structures, the next node corresponding to a portion ofthe input data string; multiple memory devices for storing the one ormore tree data structures and for returning the next node in response toa retrieval request; and a memory manager, coupled to the tree bitmapnext address mechanism and the multiple memory devices, for distributingthe retrieval request to one of the multiple memory devices. Typically,although not required, each of the one or more tree data structuresinclude: a first search node; a first child array including a firstinternal node and a second search node; and a first leaf array includingmultiple first leaf array entries; wherein the first search nodeincludes a pointer to the first child array; wherein the first internalnode includes a pointer to the first leaf array; and wherein the secondsearch node includes a pointer to one of the multiple first leaf arrayentries.

BRIEF DESCRIPTION OF THE DRAWINGS

The appended claims set forth the features of the invention withparticularity. The invention, together with its advantages, may be bestunderstood from the following detailed description taken in conjunctionwith the accompanying drawings of which:

FIGS. 1A-E are block diagrams or other illustrations of a known treebitmap system;

FIG. 2A is a block diagram an enhanced tree bitmap data structure usedin one embodiment;

FIG. 2B is a block diagram an enhanced tree bitmap data structure usedin one embodiment;

FIG. 3A is a block diagram of a process used in one embodiment toperform a longest prefix matching operation using a tree bitmap;

FIGS. 3B-C illustrate pseudo code of processes used in one embodiment toadd and delete nodes from a tree bitmap;

FIG. 4 is a block diagram of one embodiments generating and/or using atree bitmap data structure to determine a longest prefix match;

FIG. 5 is a block diagram of one embodiments generating and/or using atree bitmap data structure to determine a longest prefix match;

FIG. 6A illustrates search request and result message formats used inone embodiment;

FIG. 6B illustrates one format of node data elements used in oneembodiment;

FIG. 6C illustrates a process used in one embodiment to determine anaddress of a next relevant node or element in one embodiment of a treebitmap data structure;

FIG. 7 illustrates a process used in one embodiment to extract data froma received packet or other information, forward such data to a treebitmap system, and processing the received packet or other informationaccording to a result received from the tree bitmap system; and

FIGS. 8A-D illustrate processes used in one embodiment to perform a treebitmap longest prefix or other lookup operation.

DETAILED DESCRIPTION

Methods and apparatus are disclosed for generating and using enhancedtree bitmap data structures in determining a longest prefix match, suchas in a router, packet switching system, or other communications orcomputer component, device, or system. Embodiments described hereininclude various elements and limitations, with no one element orlimitation contemplated as being a critical element or limitation. Eachof the claims individually recites an aspect of the invention in itsentirety. Moreover, some embodiments described may include, but are notlimited to, inter alia, systems, networks, integrated circuit chips,embedded processors, ASICs, methods, and computer-readable mediumcontaining instructions. The embodiments described hereinafter embodyvarious aspects and configurations within the scope and spirit of theinvention, with the figures illustrating exemplary and non-limitingconfigurations.

As used herein, the term “packet” refers to packets of all types or anyother units of information or data, including, but not limited to, fixedlength cells and variable length packets, each of which may or may notbe divisible into smaller packets or cells. The term “packet” as usedherein also refers to both the packet itself or a packet indication,such as, but not limited to all or part of a packet or packet header, adata structure value, pointer or index, or any other part oridentification of a packet. Moreover, these packets may contain one ormore types of information, including, but not limited to, voice, data,video, and audio information. The term “item” is used herein to refer toa packet or any other unit or piece of information or data.

The term “system” is used generically herein to describe any number ofcomponents, elements, sub-systems, devices, packet switch elements,packet switches, routers, networks, computer and/or communicationdevices or mechanisms, or combinations of components thereof. The term“computer” is used generically herein to describe any number ofcomputers, including, but not limited to personal computers, embeddedprocessors and systems, control logic, ASICs, chips, workstations,mainframes, etc. The term “device” is used generically herein todescribe any type of mechanism, including a computer or system orcomponent thereof. The terms “task” and “process” are used genericallyherein to describe any type of running program, including, but notlimited to a computer process, task, thread, executing application,operating system, user process, device driver, native code, machine orother language, etc., and can be interactive and/or non-interactive,executing locally and/or remotely, executing in foreground and/orbackground, executing in the user and/or operating system addressspaces, a routine of a library and/or standalone application, and is notlimited to any particular memory partitioning technique. The steps,connections, and processing of signals and information illustrated inthe figures, including, but not limited to any block and flow diagramsand message sequence charts, may be performed in the same or in adifferent serial or parallel ordering and/or by different componentsand/or processes, threads, etc., and/or over different connections andbe combined with other functions in other embodiments in keeping withinthe scope and spirit of the invention.

Moreover, the terms “network” and “communications mechanism” are usedgenerically herein to describe one or more networks, communicationsmediums or communications systems, including, but not limited to theInternet, private or public telephone, cellular, wireless, satellite,cable, local area, metropolitan area and/or wide area networks, a cable,electrical connection, bus, etc., and internal communications mechanismssuch as message passing, interprocess communications, shared memory,etc.

The term “storage mechanism” includes any type of memory, storage deviceor other mechanism for maintaining instructions or data in any format.“Computer-readable medium” is an extensible term including any memory,storage device, storage mechanism, and other storage and signalingmechanisms including interfaces and devices such as network interfacecards and buffers therein, as well as any communications devices andsignals received and transmitted, and other current and evolvingtechnologies that a computerized system can interpret, receive, and/ortransmit. The term “memory” includes any random access memory (RAM),read only memory (ROM), flash memory, integrated circuits, and/or othermemory components or elements. The term “storage device” includes anysolid state storage media, disk drives, diskettes, networked services,tape drives, and other storage devices. Memories and storage devices maystore computer-executable instructions to be executed a processor and/orcontrol logic, and data which is manipulated a processor and/or controllogic. The term “data structure” is an extensible term referring to anydata element, variable, data structure, data base, and/or one or more oran organizational schemes that can be applied to data to facilitateinterpreting the data or performing operations on it, such as, but notlimited to memory locations or devices, sets, queues, trees, heaps,lists, linked lists, arrays, tables, pointers, etc. A data structure istypically maintained in a storage mechanism. The term “associativememory” refers to all types of known or developed associative memories,including, but not limited to binary and ternary content-addressablememories, hash tables, TRIE and other data structures, etc.

The term “one embodiment” is used herein to reference a particularembodiment, wherein each reference to “one embodiment” may refer to adifferent embodiment, and the use of the term repeatedly herein indescribing associated features, elements and/or limitations does notestablish a cumulative set of associated features, elements and/orlimitations that each and every embodiment must include, although anembodiment typically may include all these features, elements and/orlimitations. In addition, the phrase “means for xxx” typically includescomputer-readable medium containing computer-executable instructions forperforming xxx.

In addition, the terms “first,” “second,” etc. are typically used hereinto denote different units (e.g., a first element, a second element). Theuse of these terms herein does not necessarily connote an ordering suchas one unit or event occurring or coming before the another, but ratherprovides a mechanism to distinguish between particular units. Moreover,the phrases “based on x” and “in response to x” are used to indicate aminimum set of items x from which something is derived or caused,wherein “x” is extensible and does not necessarily describe a completelist of items on which the operation is performed, etc. Additionally,the phrase “coupled to” is used to indicate some level of direct orindirect connection between two elements or devices, with the couplingdevice or devices modify or not modifying the coupled signal orcommunicated information. The term “subset” is used to indicate a groupof all or less than all of the elements of a set. Moreover, the term“or” is used herein to identify an alternative selection of one or more,including all, of the conjunctive items.

Methods and apparatus are disclosed for generating and using an enhancedtree bitmap data structure in determining a longest prefix match, suchas in a router, packet switching system. One embodiment organizes thetree bitmap to minimize the number of internal nodes that must beaccessed during a lookup operation. A pointer is included in each of thetrie or search nodes to the best matching entry in the leaf or resultsarray of the parent, which allows direct access to this result withouthaving to parse a corresponding internal node. Moreover, one embodimentstores the internal node for a particular level as a first element inits child array. Additionally, one embodiment uses a general purposelookup engine that can traverse multiple tree bitmaps or other datastructures simultaneously, and perform complete searches, partialsearches, and resume partial searches such as after receiving additionaldata on which to search.

One embodiment includes an enhancement to the tree bitmap data structureand associated lookup and update schemes. These typically improve lookupperformance and may save a memory access for certain hardwareembodiments. One embodiment organizes the tree bitmap in such a way thatat most one internal node access is required per lookup. For example,one embodiment modifies the tree bitmap structure so as to avoid havingto access the internal node I2 in the access sequence S1, S2, S3, I3,I2, and L2 (i.e., the sequence previously described in relation to FIG.1E). In this example and also referring to FIG. 1E, the matching leafnode L2 (116A) is determined after parsing the internal bitmap in I2(115). An analysis of this access sequence results in the observationthat for every lookup which passes through node S3 (113), the subsequentparsing of the internal bitmap I2 (115) always yields the same matchingleaf node L2 (116). Thus, in one embodiment, a new tree bitmap datastructure and associated lookup and update schemes are used to avoidparsing the internal bitmap in I2 (122) in this exemplary lookupsequence.

One embodiment uses a data structure that includes a first search node,a first child array including a first internal node and a second searchnode, and a first leaf array including multiple first leaf arrayentries. Typically, the first search node includes a pointer to thefirst child array, the first internal node includes a pointer to thefirst leaf array; and the second search node includes a pointer to oneof the multiple first leaf array entries.

In one embodiment, the first internal node is the first element of thefirst child array. In one embodiment, the pointer of the first internalnode and the pointer of the second search node indicate different firstleaf array entries. In one embodiment, the data structure furtherincludes a second child array, wherein the second search node includes apointer to the second child array. In one embodiment, the data structurefurther includes a second leaf array including multiple second leafarray entries, wherein the second child array includes a second internalnode, the second internal node including a pointer to the second leafarray. In one embodiment, the second internal node is the first elementof the second child array. In one embodiment, the second child arrayincludes a third search or end node, wherein the second search or endnode includes a pointer to one of multiple second leaf array entries. Inone embodiment, the pointer of the second internal node and the pointerof the third search or end node indicate different second leaf arrayentries. In one embodiment, the first search node represents a stride ofa first length and the second search node represents of a stride of asecond length, wherein the first and second lengths are different. Inone embodiment, the first search node includes a first indicator of thefirst length and the second search node includes a second indicator ofthe second length.

One embodiment traverses a tree data structure representing multipleprefixes partitioned into multiple strides of a number of tree levelsgreater than one, each of the multiple strides represented by a treebitmap and indications of child paths represented by an extendingbitmap. In one embodiment, a search node at a current level within thetree data structure is received. A current best match identifier isupdated in response to determining if a new best match exists. A currentlevel extending bitmap is indexed into in determining whether or not amatching next level node exists. In one embodiment, this traversal isrepeated until a matching next level node does not exist, and then theinternal node indicated by the current level search node is retrievedand a search result is identified based on the current best matchidentifier or based on a pointer in the current level search node to aleaf node. In one embodiment, in response to determining the search nodedoes not exist at the current level, an end node indexed into toidentify the search result. In one embodiment, the current best matchidentifier is updated based on a pointer in the end node.

One embodiment traverses a tree data structure stored in one or morecomputer-readable mediums based on an input search data string.Typically, a search progression context of a partially completed treetraversal is received, in which the search progression context typicallyincludes a next node address or some other node indicator. The traversalof the tree data structure is resumed from this node a next portion ofthe input string. One embodiment distributes lookup request thattypically includes the next node address to one of multiple memorydevices. A lookup result is received from one of the multiple memorydevices, the lookup result including a search node. A current best matchidentifier is updated in response to determining if a new best matchexists. A current level extending bitmap of the search node is indexedinto to determine whether or not a matching next level node exists. Anew value of the next node address is generated, as is a new value forthe search progression context.

In one embodiment, the search progression context further includes abest match indication, and a length of input search data string used. Inone embodiment, the best match indication includes a match flag and aleaf pointer. In one embodiment, multiple tree data structures arestored in the computer-readable mediums, and these tree data structurescan be simultaneously traversed.

One embodiment apparatus for traversing nodes of one or more tree datastructures based on an input data string includes a tree bitmap nextaddress mechanism for determining a memory address of a next node of aparticular tree data structure of one or more tree data structures, thenext node corresponding to a portion of the input data string, multiplememory devices for storing one or more tree data structures and forreturning the next node in response to a retrieval request; and a memorymanager, coupled to the tree bitmap next address mechanism and themultiple memory devices, for distributing the retrieval request to oneof the multiple memory devices. Typically, each of one or more tree datastructures includes a first search node, a first child array including afirst internal node and a second search node, and a first leaf arrayincluding multiple first leaf array entries. In one embodiment, thefirst search node includes a pointer to the first child array, the firstinternal node includes a pointer to the first leaf array; and the secondsearch node includes a pointer to one of multiple first leaf arrayentries.

In one embodiment, one or more tree data structures includes nodes of atleast two different trees. In one embodiment, tree bitmap next addressfurther determines one of the multiple memory devices and provides anindication of one of the multiple memory devices to the memory manager.In one embodiment, the next node includes an indication of a particularone of the multiple memory devices, wherein the memory managerdistributes the retrieval request to the particular one of the multiplememory devices. In one embodiment, the multiple memory devices includesa first memory device of a first type and a second memory device of asecond type, wherein the first and second types are different. In oneembodiment, the first memory type stores a first-level node for each ofthe tree data structures.

FIG. 2A illustrates one such embodiment with search nodes S1(211), S2(212) and S3 (213), internal nodes I1 (221), I2 (224), and I3 (214), andleaf arrays LA1 (222), LA2 (215), LA3 (223), leaf nodes L1(222A-B), L2(215A-B), and L3 (223A-B) and their interconnections by pointers. Note,nodes illustrated in solid lines are the nodes accessed during a treebitmap lookup example described herein after. Also, as shown in FIG. 2A,pointers 220, 230, and 240 point directly from their respective searchnode 212, 213, and 225 to a parent's leaf node 222A, 215A, and 223B(corresponding the best matching entry). Also, note that FIG. 2A showsonly one path, while search nodes of other paths will point to differentleaf nodes (222A-B, 215A-B, 223A-B) within the leaf arrays (222, 215,223). In one embodiment, at control time (e.g., when the tree bitmap isbeing programmed), it is known that leaf L2 (215A) contains is thelongest match corresponding to node S3 (213). So, by directly storing apointer to leaf node L2 (215A) in node S3 (213), then I2 (224) will notneed to be accessed before accessing leaf L2 (215) in the aforementionedaccess sequence.

In one embodiment, search node S1 (211), S2 (212), S3 (213) and S4 (225)each respectfully include a parent_best_leaf pointer (210, 220, 230, and240) to the best matching leaf in their corresponding parent leaf array.Shown are search node S2 (212) having pointer 220 to leaf node L1 (222A)in leaf array LA1 (222), search node S3 (213) having pointer 230 to leafnode L2 (215A) in leaf array LA2 (215), and search node S4 (225) havingpointer 240 to leaf node L3 (23B) in leaf array LA3 (223). In oneembodiment, a zero or null parent_best_leaf pointer indicates that thereis no updated such longest matching prefix in the parent node.

In certain embodiments, minimizing the size of a node is very important.In one embodiment, space in a search node is reclaimed from prior treebitmap implementations by freeing up the internal node pointer in asearch node and by placing the internal node as the first node in thechild array. Then, an internal node can be accessed through a childpointer in the search node, and the freed up internal node pointer spacein the node structure of a search node (from a prior implementation) isused to store the pointer to the best matching leaf node in the parentleaf array. Referring to the example, the internal node pointer 235 inS3 (i.e., S3→I3), is replaced with the linkage S3→L2 (230), where L2 isthe longest match in level 2 corresponding to S3 (213).

FIG. 2B illustrates one embodiment of a new tree bitmap data structure.As shown, the internal node is placed as the first element in the childarray of the search node. Hence the children as well as the internalnode are accessed using the same pointer. For example, internal node I1(261) is the first element of child array 260, and internal node I2(281) is the first element of child array 280.

In more detail, search node S1 (250) includes a pointer 256 to childarray 260, which includes internal node I1 (261) and child elements 265.Internal node I1 (261) includes a pointer 267 to leaf array LA1 (270),which may include zero or more elements, including element leaf node L1(271), which, in this example, is the best leaf parent result for searchnode S2 (262). Note, child elements 265 includes search node S2 (262),which includes pointer 268 directly to leaf node L1 271. Note, for easeof reader understanding, a string of dots are used in child elements 265and in leaf array LA1 (270) to represent more possible search nodes inchild elements 265 and pointers to entries in leaf array LA1 (270).Search node S2 (262) also includes pointer 266 to child array 280, whichincludes internal node I2 (281) and child elements 285, including endnode E3 (282). Internal node I2 (281) includes pointer 277 to leaf arrayLA2 (290). End node E3 (282) includes pointer 288 directly to leaf nodeL2 (291), which is the best leaf parent result for end node E3 (282).

Describing one embodiment in generalized terms, the internal node I_(k)of search node S_(k) is accessed only if S_(k) is not extending prefixesfor a particular lookup. If S_(k) is extending prefixes, then I_(k)never needs to be accessed. In other words, in one embodiment, it isnever the case that both I_(k) and S_(k+1) need to be accessed in thesame lookup. Therefore, both I_(k) and S_(k+1) typically may be placedin the same memory module. In one embodiment, the internal node addressI_(k) is remembered in the lookup, if the ‘parent_has_match’ flag is setin search node S_(k+1) at the next level. With the new scheme, if‘parent_best_leaf pointer’ in S_(k+1) is non zero, it points directly tothe leaf node at level ‘k’ which is the longest matching prefix. In oneembodiment, the above node structure modifications would apply to alltree bitmap nodes except internal nodes and leaf nodes.

FIG. 3A illustrates a process used in one embodiment to perform a lookupon a tree bitmap. Processing begins with process block 300, and proceedsto process block 302, wherein the search starts with the root node atlevel k=0. Next, in process block 304, the current_best_leaf isinitialized to zero=0(e.g., no match so far) and the parent_best_leafpointer is initialized to zero=0(e.g., no match so far.)

Next, as determined in process block 306, if the current node is asearch node S_(k)(e.g., not an end node E_(k)), then as determined inprocess block 308, if the parent_best_leaf pointer in S_(k) is non-zero,then in process block 310, the current_best_leaf is set to the value ofparent_best_leaf pointer.

Next, in process block 312, the ‘extending bitmap’ of S_(k) is indexedinto using the next few bits from the lookup key depending on thestride. If, as determined in process block 314, S_(k) is extendingprefixes, then in process block 316, the address of the next level nodeis calculated in the children array (typically including an adjustmentto account for internal node I_(k) being the first node in the childrenarray). Next, in process block 318, the node at level k+1 is retrieved,and processing returns to process block 306.

Otherwise, S_(k) is not extending prefixes (as determined in processblock 314), then, in process block 320, the internal node I_(k) isretrieved, wherein I_(k) is the first element in the children array ofS_(k). If, as determined in process block 322, there is a longestmatching prefix in I_(k) by parsing the internal bitmap, then, inprocess block 324, the result is retrieved from the leaf node at levelk, and processing is complete as indicated by process block 338.Otherwise, in process block 326, the result is retrieved using the savedcurrent_best_leaf to directly access the leaf corresponding to thelongest prefix so far, and processing is complete as indicated byprocess block 338.

Otherwise, in process block 306, the current node was determined to bean end node, and processing proceeds to process block 330. If, asdetermined in process block 330, if parent best leaf pointer in E_(k) isnon-zero, then the current_best_leaf is set to the value ofparent_best_leaf pointer in process block 332.

Next, as determined in process block 334, if there is a longest matchingprefix in E_(k), then in process block 336 the result is retrieved fromthe leaf node at level K, and processing is complete as indicated byprocess block 338. Otherwise, in process block 326, the result isretrieved using the saved current_best_leaf to directly access the leafcorresponding to the longest prefix so far, and processing is completeas indicated by process block 338.

FIG. 3B illustrates a process used in one embodiment to update theparent_(—best)_leaf_pointers when inserting prefixes into a tree bitmapdata structure when a leaf node is added. Let P_(k) be the prefixinserted at level k. Let S_(k) be the corresponding search node. LetSet_(k+1)be the set of those nodes in the child array of S_(k) which arethe descendents of P_(k). In other words, P_(k) is a prefix of allsearch nodes in Set_(k+1). In one embodiment, Set_(k+1) is the set ofall nodes in which the ‘parent_has_match’ flag need to be set when P_(k)is inserted.

In one embodiment in software, the following additional variables aremaintained along with the ‘parent_best_leaf pointer’ in each searchnode. Note, in one embodiment, these are required only in the controlsoftware node structure and not in the hardware structure. Thebestleaf_offset(S_(k+1)) is basically the offset of the leaf pointed toby parent_best_leaf(S_(k+1)) in its leaf array. The ‘bestleaf_length’ isthe length of the prefix pointed to by parent_best_leaf (S_(k+1)).

The following are the definitions of terms/functions/variables used inthe pseudo code illustrated in FIG. 3B. Children_array(S_(k)) is thechild array pointer of search node S_(k). Bestleaf_offset(S_(k+1)) isthe value of the software only ‘bestleaf_offset’ variable of search nodeS_(k+1). Parent_best_leaf(S_(k+1)) is the value of the newly introduced‘parent_best_leaf pointer’ in search node S_(k+1).Bestleaf_length(S_(k+1)) is the value of the software only‘bestleaf_length’ variable of search node S_(k+1).New_leaf_array_base(P_(k)) is the address of the location in the treebitmap, when a new prefix is inserted in an existing leaf array, towhich the entire leaf array along with the inserted prefix P_(k) iscopied.

Basically, as described in the pseudo code illustrated in FIG. 3B, theactual insertion of the prefix proceeds same as prior implementations,with the addition of updating the parent_best_leaf_pointers in the nextlevel search nodes, instead of updating the parent has_match flag. For atree bitmap data structure that is in a consistent state with allparent_best_leaf pointers pointing to the correct leaves, the pseudocode illustrated in FIG. 3B shows how all the parent_best_leaf pointersare again brought to a consistent state after a prefix insert.

In addition, when a new search node S_(k+1) is inserted into the childarray of S_(k) (e.g., when new branches of the tree are created as aresult of Prefix Insert), the parent_best_leaf(S_(k+1)) needs to bedetermined. Essentially, the offset of the leaf node in the leaf arrayL_(k) of S_(k) which is the longest prefix corresponding to S_(k+1) isdetermined by parsing the internal bitmap in the internal node I_(k) ofS_(k).

In addition, the parent_best_leaf_pointers must be updated when a prefixis deleted. Let P_(k) be the prefix being deleted at level k. Let S_(k)be the corresponding search node. Let Set_(k+1) be the set of thosenodes in the child array of S_(k) for whom P_(k) is the best leaf. FIG.3C illustrates a process used in one embodiment to update theparent_best_leaf_pointers in the child nodes of the search node fromwhich the prefix is deleted.

FIG. 4 illustrates one embodiment of a system 400 such as, but notlimited to a computer or communications system, for implementing a treebitmap data structure. In one embodiment, system 400 uses such a treebitmap data structure for determining longest prefix matches accordingto the invention. In one embodiment, system 400 programs another device,such as traversing engine 500 (FIG. 5), via interface 404 with a treebitmap data structure.

In one embodiment, system 400 includes a processor 401, memory 402,storage devices 403, and optionally interface 404, which are typicallycoupled via one or more communications mechanisms 409 (shown as a busfor illustrative purposes.) Various embodiments of system 400 mayinclude more or less elements. The operation of system 400 is typicallycontrolled by processor 401 using memory 402 and storage devices 403 toperform one or more scheduling tasks or processes. Memory 402 is onetype of computer-readable medium, and typically comprises random accessmemory (RAM), read only memory (ROM), flash memory, integrated circuits,and/or other memory components. Memory 402 typically storescomputer-executable instructions to be executed by processor 401 and/ordata which is manipulated by processor 401 for implementingfunctionality in accordance with the invention. Storage devices 403 areanother type of computer-readable medium, and typically comprise solidstate storage media, disk drives, diskettes, networked services, tapedrives, and other storage devices. Storage devices 403 typically storecomputer-executable instructions to be executed by processor 401 and/ordata which is manipulated by processor 401 for implementingfunctionality in accordance with the invention.

FIG. 5 illustrates a block diagram of one embodiment for traversing ahierarchal data structure, including, but not limited to a tree bitmapor other tree data structure. A requesting device 501, such as aprocessor or other control logic, generates lookup requests that arereceived by traversing engine 500, and stores them in request buffer512. Maintenance processor 502 programs traversing engine 500 with oneor more tree bitmap and/or other data structures, as traversing enginecan simultaneously be used to perform searches on multiple and evenindependent tree bitmap and/or other data structures. In one embodiment,requesting device 501 and/or maintenance processor correspond to system400 (FIG. 4). In one embodiment, requesting device 501 and/ormaintenance processor 502 are included in traversing engine 500.

In one embodiment, traversing engine 500 includes a request buffer 512to receive and buffer search requests, a memory manager 520 to controlread and write operations to memory device and control 521-529 and toSRAM and control 530, with results being directed to tree bitmap nextaddress logic 514 or output queue 535. Output queue 535 communicatessearch results to requesting device 501. Tree bitmap next address logic514 processes search requests received from request buffer 512 andintermediate results received from memory devices and controls 521-529and from SRAM and control 530, and possibly determines the memoryaddress of the next node and forwards the memory read request to memorymanager 520.

Search requests received or generated by traversing engine 500 mayinclude a full or partial string based on which to find a longestmatching prefix or other result. For example, in one embodiment,traversing engine 500 includes the ability to search based on a firstportion of a lookup string, return a result, and then continue thesearch from where it left off based on the result and an additionalportion of the lookup string. In addition, in one embodiment, traversingengine 500 will continue to search through the data structure until aresult is received, search data is exhausted, or a stop node (describedfurther hereinafter) is encountered.

Formats used in one embodiment of a search request are shown in FIG. 6A.Initial search request 601 includes a search type field indicating aninitial (versus a continued) search request and a search data fieldincluding the information on which to match. Continued search request602 includes a search type field indicating a continued search, a startaddress field indicating from where to resume the search, a search datafield including an additional portion of the lookup string, a valid leafso far flag and pointer to best leaf so far field, where this flagindicates whether pointer to best leaf so far field is populated withthe corresponding pointer (determined during a previous portion of thesearch.)

FIG. 6A additionally illustrates formats used in one embodiment of asearch response. Response (continuing search) result 603 includes asearch result type field, a next node address field, a valid leaf so farflag, a pointer to best leaf so far field, and a length of search dataused field. Response (leaf access) result 604 includes a search resulttype field, and the resulting leaf node data field.

One or more tree bitmap or other data structures are loaded into and canbe retrieved by maintenance processor 502 (FIG. 5) by submittingrequests to update control 539, which sends update requests to memorymanager 520, and can receive information from memory devices andcontrols 521-529 and from SRAM and control 530.

FIG. 6B illustrates the format of nodes or data structure elements usedin one embodiment. Search/end/stop node 611 includes a node type field,a child array cluster size which indicated a stride size used in thecurrent node, thus data structure can use variable lengths strides andnodes. Search/end/stop node 611 further includes the extending bitmap,children (e.g., child arrays) pointer field, best leaf so far pointer,internal node exist flag, and an error correcting code field. Internalnode 612 includes a node type field, leaf array pointer field, best leaftill now pointer field, internal bitmap field, and error correcting codefield. Leaf node 613 includes a node type field, an associative returndata field, and an error correcting code field. Skip node 614 includes anode type field, compared data field, compared length field, best leafso far field, children (e.g., child arrays) pointer field, and an errorcorrecting code field.

Returning to FIG. 5, search requests, such as, but not limited to thosedescribed herein, are received by request buffer 512. If the memoryaddress of the node is readily available based on the received searchrequest, the request is forwarded directly to memory manager 520.Otherwise, the request is forwarded to tree bitmap next address logic514, wherein the memory address is calculated. Note, that tree bitmapnext address logic 514 also receives memory read results and calculatesthe memory address of the next node, or forwards the memory read result(e.g., node) to output queue 535.

FIG. 6C illustrates a process used in one embodiment to calculate ordetermine the next address (e.g., the address of the relevant next nodeor element in the data structure.) Processing begins with process block650, and proceeds to process block 652, wherein the current stridelength of the next portion of the lookup string and the child bitmap areretrieved. Note, in one embodiment, the stride length of an entry canvary among each entry. Moreover, one embodiment supports varying sizesof child array, with this size being identified by the child arraycluster size. Next, in process block 654, the number of ones in theentry's child bitmap up to the position matching the lookup string arecounted.

Thus, this count identifies which element is the next one of interest.In process block 656, the next address is calculated based on the childpointer plus the count multiplied by the width of a pointer field. Then,in process block 658, the lookup request including the determined nextaddress, memory bank and channel to use is forwarded to the memorymanager, and processing is complete as indicated by process block 659.

The processing by requesting device 501 (FIG. 5) and traversing engine500 is further described by the flow diagrams illustrated in FIGS. 7,and 8A-D, to which we now turn.

FIG. 7 illustrates a process used in one embodiment by requesting device501 (FIG. 5). Processing begins with process block 700, and proceeds toprocess block 702 wherein a packet or other information is received.Next, in process block 704, a memory search request, such as initialsearch request 601 (FIG. 6A), is forwarded to traversing engine 500(FIG. 5). Next, in process block 706, the result is received fromtraversing engine 500. As determined in process block 708, if the searchis not completed (e.g., there are more bits to provide to traversingengine in a search request, such as for a continued search request 602of FIG. 6A), processing returns to process block 704 to generate andtransmit the search request. Otherwise, in process block 710, the packetor other information is processed based on the received result.Processing is complete for this search as indicated by process block712.

FIGS. 8A-D illustrate a process used in one embodiment to traverse thetree bitmap or other data structure. Processing begins with processblock 800, and proceeds to process block 802, wherein the initial orcontinued search request is received. Next, as determined in processblock 804, if the first memory access should be performed in SRAM andcontrol 530, then the SRAM lookup address is determined in process block806, and the memory access (i.e., lookup) request is forwarded to theSRAM controller for performing the memory access in process block 808.Otherwise, or continuing via connector 8A (811), in process block 810,the lookup request is forwarded to one of the external memory devicesbased on some distribution scheme for the memory devices available toservice the request. In one embodiment, each of the one or more treebitmap or other data structures is replicated in each of the externalmemories. In one embodiment, certain of the tree bitmap or other datastructures populate a subset of the external memories.

Next, in process block 812, the lookup result is received. If, asdetermined in process block 814, the lookup result includes a skip node,then processing proceeds via connector 8B (816) to connector 8B (830) inFIG. 8B. Otherwise, if, as determined in process block 818, the lookupresult includes an internal node, then processing proceeds via connector8C (820) to connector 8C (850) in FIG. 8C. Otherwise, if as determinedin process block 822, the lookup result includes a leaf node, then inprocess block 824, the return value of the lookup is sent in processblock 824, and processing is complete as indicated by process block 826.Otherwise, processing proceeds to via connector 8D (828) to connector 8D(870) in FIG. 8D.

Turning to FIG. 8B, processing continues via connector 8B (830) or 8E(840). Commencing from connector 8B (830), as determined in processblock 832, if there is a best leaf corresponding to the current node,then this best leaf is stored as the current best leaf discovered so farin the search in process block 834. Next, as determined in process block836, the skip bits provided in the skip node match the next data bits ofthe lookup string, then, in process block 838, the specified address inthe skip node is used as the next address value, and processing returnsvia connector 8A (839) to connector 8A (811) in FIG. 8A. The skip nodeallows a string of search data to be compared against a programmedstring which may correspond to one or more tries, and thus, may be usedto save memory accesses and lookup time. This skip node feature isespecially useful when there are long strings in the lookup string whichdo not vary, such as in an IPv6 lookup.

Otherwise, or continuing from connector 8E (840), if a best match hasbeen determined in process block 842, then this best match value is usedas the next address, and processing proceeds via connector 8A (847) toconnector 8A (811) FIG. 8A. Otherwise, a best match result was notlocated, and the no match result is sent in process block 844, andprocessing of this search is completed as indicated by process block845.

Turning to FIG. 8C, commencing from connector 8C (850), as determined inprocess block 852, if there is a best leaf corresponding to the currentnode, then this best leaf is stored as the current best leaf discoveredso far in the search in process block 854. Next, as determined inprocess block 856, if the offset bit flag is set in the tree bitmap(i.e., the tree bitmap is to be parsed), then, in process block 858, theaddress of the leaf node is calculated in process block 858, andprocessing proceeds via connector 8A (859) to connector 8A (811) FIG.8A. Otherwise, processing proceeds via connector 8E (857) to connector8E (840) in FIG. 8B.

Turning to FIG. 8D, commencing from connector 8D (870), as determined inprocess block 872, if there is a best leaf corresponding to the currentnode, then this best leaf is stored as the current best leaf discoveredso far in the search in process block 873. Next, as determined inprocess block 874, if the corresponding bit in the external bitmap isnot set (e.g., there is not an external lookup for this lookup), thenprocessing proceeds to process block 876. If the child node is not aninternal node, then as determined in process block 880, if there is amatch of the lookup string, then in process block 881 the next addressis set to the best address, and processing proceeds via connector 8A(883) to connector 8A (811) FIG. 8A. Otherwise, in process block 882, ano match result is sent in process block 882, and processing iscompleted as indicated by process block 883. Otherwise, if an internalnode as determined in process block 876, then in process block 878, thenext address is set to the value of the child pointer, and processingproceeds via connector 8A (879) to connector 8A (811) FIG. 8A.

Otherwise, the next address of the child node is calculated in processblock 884. If the current node is a stop node (e.g., indicates a stoptraversal indication) as determined in process block 886, then the stateof the search is returned or sent in process block 888, and processingis completed as indicated by process block 889. Otherwise, processingproceeds via connector 8A (887) to connector 8A (811) FIG. 8A.

In view of the many possible embodiments to which the principles of ourinvention may be applied, it will be appreciated that the embodimentsand aspects thereof described herein with respect to thedrawings/figures are only illustrative and should not be taken aslimiting the scope of the invention. For example and as would beapparent to one skilled in the art, many of the process block operationscan be re-ordered to be performed before, after, or substantiallyconcurrent with other operations. Also, many different forms of datastructures could be used in various embodiments. The invention asdescribed herein contemplates all such embodiments as may come withinthe scope of the following claims and equivalents thereof.

1. A computer-readable medium having stored thereon a data structure,the data structure comprising: a first search node; a first child arrayincluding a first internal node and a second search node; and a firstleaf array including a plurality of first leaf array entries; whereinthe first search node includes a pointer to the first child array;wherein the first internal node includes a pointer to the first leafarray; and wherein the second search node includes a pointer to one ofthe plurality of first leaf array entries.
 2. The computer-readablemedium of claim 1, wherein the first internal node is the first elementof the first child array.
 3. The computer-readable medium of claim 1,wherein the pointer of the first internal node and the pointer of thesecond search node indicate different said first leaf array entries. 4.The computer-readable medium of claim 1, comprising a second childarray; and wherein the second search node includes a pointer to thesecond child array.
 5. The computer-readable medium of claim 4,comprising a second leaf array including a plurality of second leafarray entries; and wherein the second child array includes a secondinternal node, the second internal node including a pointer to thesecond leaf array.
 6. The computer-readable medium of claim 5, whereinthe second internal node is the first element of the second child array.7. The computer-readable medium of claim 6, wherein the second childarray includes a third search or end node, wherein said second search orend node includes a pointer to one of the plurality of second leaf arrayentries.
 8. The computer-readable medium of claim 7, wherein the pointerof the second internal node and the pointer of the third search or endnode indicate different said second leaf array entries.
 9. Thecomputer-readable medium of claim 1, wherein the first search noderepresents a stride of a first length and the second search noderepresents of a stride of a second length, wherein the first and secondlengths are different.
 10. The computer-readable medium of claim 9,wherein the first search node includes a first indicator of the firstlength and the second search node includes a second indicator of thesecond length.
 11. A method performed using a tree data structurerepresenting a plurality of prefixes partitioned into a plurality ofstrides of a number of tree levels greater than one, each of theplurality of strides represented by a tree bitmap and indications ofchild paths represented by an extending bitmap, the method comprising:(a) retrieving a search node at a current level within the tree datastructure; (b) updating a current best match identifier in response todetermining if a new best match exists; (c) indexing into a currentlevel extending bitmap to determine whether or not a matching next levelnode exists; (d) in response to said determining the matching next levelnode exists, repeating step (a), (b) and (c) for the current level beinga next level identified based on said indexing into the current levelextending bitmap to determine an offset within an internal node indictedby the search node; and (e) in response to said determining the matchingnext level node does not exist, performing steps including: retrievingan internal node indicated by the current level search node; andidentifying a search result based on the current best match identifieror based on a pointer in the current level search node to a leaf node.12. The method of claim 11, comprising: in response to determining thesearch node does not exist at the current level, indexing into an endnode to identify the search result.
 13. The method of claim 12,comprising updating the current best match identifier based on a pointerin the end node.
 14. An apparatus for determining a search result basedon a tree data structure representing a plurality of prefixespartitioned into a plurality of strides of a number of tree levelsgreater than one, each of the plurality of strides represented by a treebitmap and indications of child paths represented by an extendingbitmap, the apparatus comprising: means for retrieving a search node ata current level within the tree data structure; means for updating acurrent best match identifier in response to determining if a new bestmatch exists; means for indexing into a current level extending bitmapto determine whether or not a matching next level node exists; means forindexing into the current level extending bitmap to determine an offsetwithin an internal node indicted by the search node; means forretrieving an internal node indicated by the current level search node;and means for identifying a search result based on the current bestmatch identifier or based on a pointer in the current level search nodeto a leaf node.
 15. The apparatus of claim 14, comprising means forindexing into an end node to identify the search result.
 16. Theapparatus of claim 15, comprising means for updating the current bestmatch identifier based on a pointer in the end node.
 17. Acomputer-readable medium containing computer-executable instructions forperforming steps using a tree data structure representing a plurality ofprefixes partitioned into a plurality of strides of a number of treelevels greater than one, each of the plurality of strides represented bya tree bitmap and indications of child paths represented by an extendingbitmap, said steps comprising: (a) retrieving a search node at a currentlevel within the tree data structure; (b) updating a current best matchidentifier in response to determining if a new best match exists; (c)indexing into a current level extending bitmap to determine whether ornot a matching next level node exists; (d) in response to saiddetermining the matching next level node exists, repeating step (a), (b)and (c) for the current level being a next level identified based onsaid indexing into the current level extending bitmap to determine anoffset within an internal node indicted by the search node; and (e) inresponse to said determining the matching next level node does notexist, performing steps including: retrieving an internal node indicatedby the current level search node; and identifying a search result basedon the current best match identifier or based on a pointer in thecurrent level search node to a leaf node.
 18. The computer-readablemedium of claim 17, having computer-executable instructions forperforming steps including: in response to determining the search nodedoes not exist at the current level, indexing into an end node toidentify the search result.
 19. The computer-readable medium of claim18, having computer-executable instructions for performing stepsincluding updating the current best match identifier based on a pointerin the end node.
 20. A method for traversing a tree data structurestored in one or more computer-readable mediums based on an input searchdata string, the method comprising performing for each of a plurality ofportions of the input search data string a set of steps including: (a)receiving a search progression context of a partially completed treetraversal, the search progression context including a next node address;(b) resuming said traversal of the tree data structure includingrepeatedly performing steps (i)-(iv) for traversing the tree datastructure corresponding to a next one of the plurality of portions ofthe input string: (i) distributing a lookup request including the nextnode address to one of a plurality of memory devices; (ii) receiving alookup result from said one of the plurality of memory devices, thelookup result including a search node; (iii) updating a current bestmatch identifier in response to determining if a new best match exists;(iv) indexing into a current level extending bitmap of the search nodeto determine whether or not a matching next level node exists; (v)generating a new value of the next node address; and (c) generating anew value for the search progression context.
 21. The method of claim20, wherein the search progression context includes a best matchindication, and a length of input search data string used.
 22. Themethod of claim 21, wherein the best match indication includes a matchflag and a leaf pointer.
 23. The method of claim 20, wherein the one ormore computer readable mediums include a plurality of different treedata structures; and wherein steps (a), (b) and (c) are performed foreach of a plurality of input search data strings corresponding to eachof the plurality of different tree data structures.
 24. Acomputer-readable medium containing computer-executable instructions forperforming a method for traversing a tree data structure based on aninput search data string, the method comprising performing for each of aplurality of portions of the input search data string a set of stepsincluding: (a) receiving a search progression context of a partiallycompleted tree traversal, the search progression context including anext node address; (b) resuming said traversal of the tree datastructure including repeatedly performing steps (i)-(iv) for traversingthe tree data structure corresponding to a next one of the plurality ofportions of the input string: (i) distributing a lookup requestincluding the next node address to one of a plurality of memory devices;(ii) receiving a lookup result from said one of the plurality of memorydevices, the lookup result including a search node; (iii) updating acurrent best match identifier in response to determining if a new bestmatch exists; (iv) indexing into a current level extending bitmap of thesearch node to determine whether or not a matching next level nodeexists; (v) generating a new value of the next node address; and (c)generating a new value for the search progression context.
 25. Thecomputer-readable medium of claim 24, wherein the search progressioncontext includes a best match indication, and a length of input searchdata string used.
 26. The computer-readable medium of claim 25, whereinthe best match indication includes a match flag and a leaf pointer. 27.The computer-readable medium of claim 24, wherein steps (a), (b) and (c)are performed for each of a plurality of input search data stringscorresponding to each of a plurality of different tree data structures.28. An apparatus for traversing nodes of one or more tree datastructures based on an input data string, the apparatus comprising: atree bitmap next address mechanism for determining a memory address of anext node of a particular tree data structure of said one or more treedata structures, the next node corresponding to a portion of the inputdata string; a plurality of memory devices for storing said one or moretree data structures and for returning the next node in response to aretrieval request; and a memory manager, coupled to the tree bitmap nextaddress mechanism and the plurality of memory devices, for distributingthe retrieval request to one of the plurality of memory devices; whereineach of said one or more tree data structures include: a first searchnode; a first child array including a first internal node and a secondsearch node; and a first leaf array including a plurality of first leafarray entries; wherein the first search node includes a pointer to thefirst child array; wherein the first internal node includes a pointer tothe first leaf array; and wherein the second search node includes apointer to one of the plurality of first leaf array entries.
 29. Theapparatus of claim 28, wherein said one or more tree data structuresincludes nodes of at least two different trees.
 30. The apparatus ofclaim 28, wherein the tree bitmap next address further determines saidone of the plurality of memory devices and provides an indication ofsaid one of the plurality of memory devices to the memory manager. 31.The apparatus of claim 30, wherein the next node includes an indicationof a particular one of the plurality of memory devices, wherein thememory manager distributes the retrieval request to the particular oneof the plurality of memory devices.
 32. The apparatus of claim 28,wherein the plurality of memory devices includes a first memory deviceof a first type and a second memory device of a second type, wherein thefirst and second types are different.
 33. The apparatus of claim 32,wherein the first memory type stores a first-level node for each of thetree data structures.
 35. An apparatus for traversing a tree datastructure stored in one or more computer-readable mediums based on aninput search data string, the apparatus comprising: means for receivinga search progression context of a partially completed tree traversal,the search progression context including a next node address; and meansfor resuming said traversal of the tree data structure; means fordistributing a lookup request including the next node address to one ofa plurality of memory devices; means for receiving a lookup result fromsaid one of the plurality of memory devices, the lookup result includinga search node; means for updating a current best match identifier inresponse to determining if a new best match exists; means for indexinginto a current level extending bitmap of the search node to determinewhether or not a matching next level node exists; means for generating anew value of the next node address; and means for generating a new valuefor the search progression context.
 36. The apparatus of claim 35,wherein the search progression context includes a best match indication,and a length of input search data string used.
 37. The apparatus ofclaim 36, wherein the best match indication includes a match flag and aleaf pointer.